"DuckDB" matching MCP servers:

A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.

A read-only DuckDB MCP server offering context-efficient analytics tools (list_datasets, describe_table, profile_column, explain, query) with a semantic layer for business rules, security guards, and disclosed truncation to help LLMs produce correct answers while minimizing token usage.

Enables read-only analytical access to local CSV, Parquet, JSON files or a DuckDB database through MCP, with table discovery, column profiling, guarded SQL querying, and explain plans for safe use with Claude Desktop and Claude Code.

Enables DuckDB database interaction through MCP, supporting SQL queries, table creation, and schema inspection with optional read-only mode.

Enables LLMs to interact with DuckDB databases through MCP tools for SQL queries, table management, data import/export, and schema inspection, with optional read-only mode for safety.

A local MCP server enabling AI assistants to query and analyze data via DuckDB SQL engine, supporting local files, memory, S3, and MotherDuck.

A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis.

A beginner-friendly MCP server that exposes a run_sql tool for querying a DuckDB employee database, returning results as Markdown tables. It enables AI assistants to run SQL queries through the Model Context Protocol.

Converts raster and vector geospatial data into H3-indexed Parquet files and serves them via a local MCP server with DuckDB SQL querying.

Read-only SQL MCP server for quantitative finance data (DuckDB) with stock quotes, financials, and historical K-lines, enabling cross-database JOIN queries.

Lets LLMs rank, compare, and connect actors and movies from local IMDb non-commercial datasets stored in DuckDB, with Wikidata enrichment.

MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.

A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.

Enables querying and updating Markdown frontmatter metadata using DuckDB SQL, with optional semantic search capabilities for finding similar documents based on content.

Answers natural-language questions against Postgres, Oracle, Snowflake, Databricks, DuckDB and SQLite via db_read(question) and get_schema(), each separately grantable. The model only proposes SQL — shape, access, dialect and query plan are checked deterministically before any rows are read, and the server refuses rather than returning an unverified answer.

Local-first MCP server for discovering, downloading, and analyzing official IBGE microdata using DuckDB and Parquet.

Analyzes Salesforce permission architecture (profiles, permission sets, groups) to support RBAC remediation. It snapshots the permission model into DuckDB and provides tools for diffs, sensitive access detection, and verified decomposition proposals.

Enables AI agents to perform professional-grade geoprocessing tasks such as buffers, overlays, reprojections, and terrain analysis with deterministic tools and verifiable provenance.

Enables AI agents to discover and execute analytical queries on a DuckDB dataset through typed MCP tools, with guarded read-only SQL support for complex calculations without direct database access.

Enables Claude to query a local DuckDB warehouse containing mock motorcycle-loan data, with tools for customer search, insights, and read-only SQL queries.